We show two sets of results applying the theory of extractors to resource-bounded Kolmogorov complexity: Most strings in easy sets have nearly optimal polynomial-time CD complexity. This extends work of Sipser Sip83] and Buhrman and Fortnow BF97]. We use extractors to extract the randomness of strings. In particular we show how to get from an arbitrary string, an incompressible string which enc...

In this paper, we present a novel approach to microaneurysm candidate extraction. To strengthen the accuracy of individual algorithms, we propose an ensemble of state-of-the-art candidate extractors. We apply a simulated annealing based method to select an optimal combination of such algorithms for a particular dataset. We also present a novel classification technique, which is based on a paral...

In previous research, Shelton et al. presented a geneticbased method for evolving feature extractors for facial recognition. The technique presented evolved feature extractors that consisted of non-uniform, overlapping patches and did not cover the entire image. In this paper, we compare the use of non-uniform, overlapping patches with uniform, overlapping patches. Our results show a statistica...

We give the first explicit construction of deterministic extractors for affine sources over F2, with entropy k ≥ log n for some large enough constant C, where n is the length of the source. Previously the best known results are by Bourgain [Bou07], Yehudayoff [Yeh11] and Li [Li11b], which require the affine source to have entropy at least Ω(n/ √ log log n). Our extractor outputs one bit with er...

This report describes a suite of program extractors which we developed by adopting and extending existing program parsing and extraction techniques or tools. This suite is called CX because it is mainly targeted at extracting facts from C and C++ programs. This suite is currently composed of four extractors: CPPX, BFX, LDX and CTSX. The main goal of creating CX is to provide a convenient set of...

We present POLYGLOTIE, a web-based tool for developing extractors that perform Information Extraction (IE) over multilingual data. Our tool has two core features: First, it allows users to develop extractors against a unified abstraction that is shared across a large set of natural languages. This means that an extractor needs only be created once for one language, but will then run on multilin...

We describe a method of cryptographically-secure key extraction from a noisy biometric source. The computational security of our method can be clearly argued through hardness of Learning Parity With Noise (LPN). We use a fuzzy commitment scheme so the extracted key is chosen by definition to have uniformly random bits. The biometric source is used as the noise term in the LPN problem. A key ide...

Randomness is used in many places in our daily lives. Some examples are gambling, statistics, algorithms, cryptography etc. For such applications one typically assumes a supply of completely unbiased and independent randim bits. This raises the problem of where to get these assumed random bits from. We could try and use natural sources of randomness such as sun spots, the stock market or the we...